Machine Learning and Computational Statistics I am looking for self-motivated (visiting) Ph.D. students / (remote) research assistants to work with me on machine learning. Fellowships / salaries are provided to qualified candidates. Any interested applicants can directly send me your CV and a brief introduction to your research interest. Please refer to the (https://zhuanlan.zhihu.com/p/651070296) for more details.

* Zhang, X., Chen, Y., Xue, B., Lin, X., and Zhang, Q., (2023). Hypervolume Maximization: A Geometric View of Pareto Set Learning. 37th Conference on Neural Information Processing Systems (NeurIPS'23) * Chen, Y., Yao, R., Yang, Y., and Chen, J., (2023). A Gromov–Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening. In Proceedings of 40th International Conference on Machine Learning (ICML'23). * Wei, T., Guo, Z., Chen, Y., and He, J., (2023). NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning. In Proceedings of 40th International Conference on Machine Learning (ICML'23). * Chen, Y., and Yang, Y., (2021). Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression. The 24th International Conference on Artificial Intelligence and Statistics (AISTATS'21).